This disclosure relates generally to object detection. More particularly, this disclosure relates to the resolution of closely spaced objects in an image.
The detection, location, and characterization of closely spaced targets and objects at a long observation range are useful in a multitude of contexts. The application of such techniques is found in space situational awareness, missile defense (including tracking as well as discrimination of targets), and astronomy research. For example, in the context of space situational awareness, the characterization of closely spaced objects may be used in the ground detection of small “intruder” satellites that may be near large geostationary earth orbit satellites.
Resolving ability in imaging, whether through a filled aperture telescope, or a plurality of telescopes utilizing interferometric techniques, is physically limited by a number of criteria, including diffraction limitations, other point spread function factors, the signal to noise ratio (SNR) of the received electromagnetic radiation, and the pixel sample size at the focal plane. For example, the empirically derived Rayleigh diffraction limit of 1.22 λ/D is generally accepted as corresponding to the minimum angular resolution at which two identically sized objects may be sufficiently resolved. The difficulty in attempting to overcome such physical limitations to resolve two or more closely spaced objects increases, however, when one object is either larger or brighter than the others.
Some statistical analysis methods may be employed to assist in resolving an image. For example, hypothesis testing techniques such as the known Pixon method may succeed in resolving images beyond the Rayleigh resolution limit, however may be limited by a high SNR requirement with very fine sampling levels. Such hypothesis testing makes educated guesses at the details of the observation (including object sizes and separations), and works backwards to get the best fit to the reconstructed and highly sampled image. This process may require extensive computation capabilities to run through what might amount to be millions of possible scenarios.
What is needed is, among other things, improvements over known techniques to resolve closely spaced objects though the use of a variety of phenomenologies, either alone or in combination.